From 41d12463fd5f9973ad1258fa2eb03589fbd816ca Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Johannes=20Sch=C3=B6nberger?= Date: Sun, 3 Nov 2013 09:45:33 +0100 Subject: [PATCH] Fix RANSAC doctest --- skimage/measure/__init__.py | 1 - skimage/measure/fit.py | 32 ++++++++++++++++++-------------- 2 files changed, 18 insertions(+), 15 deletions(-) diff --git a/skimage/measure/__init__.py b/skimage/measure/__init__.py index 108cd7d9..e5bc6d77 100755 --- a/skimage/measure/__init__.py +++ b/skimage/measure/__init__.py @@ -23,6 +23,5 @@ __all__ = ['find_contours', 'moments_central', 'moments_normalized', 'moments_hu', - 'sum_blocks', 'marching_cubes', 'mesh_surface_area'] diff --git a/skimage/measure/fit.py b/skimage/measure/fit.py index 66502ffa..d83db07d 100644 --- a/skimage/measure/fit.py +++ b/skimage/measure/fit.py @@ -551,20 +551,22 @@ def ransac(data, model_class, min_samples, residual_threshold, >>> model = EllipseModel() >>> model.estimate(data) >>> model._params - array([ 4.85808595e+02, 4.51492793e+02, 1.15018491e+03, - 5.52428289e+00, 7.32420126e-01]) + array([ -3.30354146e+03, -2.87791160e+03, 5.59062118e+03, + 7.84365066e+00, 7.19203152e-01]) + Estimate ellipse model using RANSAC: >>> ransac_model, inliers = ransac(data, EllipseModel, 5, 3, max_trials=50) - >>> # ransac_model._params, inliers - - Should give the correct result estimated without the faulty data:: - - [ 20.12762373, 29.73563061, 4.81499637, 10.4743584, 0.05217117] - [ 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, - 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, - 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49] + >>> ransac_model._params + array([ 20.12762373, 29.73563063, 4.81499637, 10.4743584 , 0.05217117]) + >>> inliers + array([False, False, False, False, True, True, True, True, True, + True, True, True, True, True, True, True, True, True, + True, True, True, True, True, True, True, True, True, + True, True, True, True, True, True, True, True, True, + True, True, True, True, True, True, True, True, True, + True, True, True, True, True], dtype=bool) Robustly estimate geometric transformation: @@ -578,10 +580,12 @@ def ransac(data, model_class, min_samples, residual_threshold, >>> dst[2] = (50, 50) >>> model, inliers = ransac((src, dst), SimilarityTransform, 2, 10) >>> inliers - array([ 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, - 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, - 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49]) - + array([False, False, False, True, True, True, True, True, True, + True, True, True, True, True, True, True, True, True, + True, True, True, True, True, True, True, True, True, + True, True, True, True, True, True, True, True, True, + True, True, True, True, True, True, True, True, True, + True, True, True, True, True], dtype=bool) """